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STORD

Cloud-based fulfillment, warehousing, and freight

Senior Data Engineer - GCP

Data EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USANo salary listedRemote

About the Job

Requirements

  • At least 5 years of data engineering experience, including at least 3 years in a cloud environment, preferably GCP.
  • Expertise in GCP services including BigQuery, Dataflow, Pub/Sub, Cloud Composer, Cloud Storage, Cloud Functions, and Cloud SQL.
  • Strong SQL skills, including experience writing complex queries for data extraction and analysis.
  • Hands-on ETL development and workflow orchestration using tools such as Apache Airflow.
  • Proficiency in Python and/or Spark for data processing and pipeline development.
  • Experience with streaming data pipelines such as Pub/Sub or Dataflow, as well as batch processing.
  • Understanding of data warehousing concepts, large datasets, and query optimization.
  • Working knowledge of data governance, security, and compliance in a cloud environment.
  • Understanding of machine learning concepts and data preparation for machine learning applications; interest in agentic AI tooling is required.
  • Strong analytical, problem-solving, and troubleshooting skills, with attention to detail.
  • Clear communication and ability to collaborate across teams.

Responsibilities

  • Design and build scalable data pipelines using GCP services such as Cloud Dataflow, Cloud Pub/Sub, Data Stream, Spark, and Cloud Composer to ingest, process, and store large datasets from multiple sources.
  • Develop, test, and maintain data models, schemas, and ETL processes using BigQuery, Cloud SQL, Spark, and Data Studio.
  • Partner with stakeholders to understand business requirements and translate them into data infrastructure solutions.
  • Optimize data pipelines for performance, scalability, and cost efficiency using GCP-native tools such as Dataproc and Bigtable.
  • Ensure data quality, integrity, and security by building validation processes and enforcing data governance, access control, and security best practices.
  • Automate workflows using Cloud Composer so pipelines run reliably and on schedule.
  • Own end-to-end pipeline and data infrastructure reliability, including monitoring, alerting, troubleshooting, and root cause analysis, in partnership with SRE and Infrastructure teams on shared GCP compute, storage, and network resources.
  • Prepare, model, and expose data for machine learning and agentic AI use cases, including governed data pipelines queried by Stord's AI tooling in production.
  • Mentor the broader data team on pipeline design and data infrastructure standards.
  • Stay current with GCP's roadmap and emerging best practices and apply relevant learnings to the platform.

Desired Qualifications

  • Bachelor's degree in Computer Science or a comparable field, or equivalent experience.
  • GCP certification such as Professional Data Engineer or Cloud Architect.
  • Experience with machine learning infrastructure on GCP, such as AI Platform and TensorFlow.
  • Familiarity with DevOps and MLOps practices, including CI/CD, infrastructure as code with Terraform, and containerization with Kubernetes and Docker on GCP.
  • Experience with other data processing frameworks, such as Apache Spark.
  • Background in logistics, supply chain, third-party logistics, or warehouse and fulfillment technology.
  • Experience working on a distributed team.

About the Company

STORD

Cloud-based fulfillment, warehousing, and freight

STORD provides logistics services (fulfillment, warehousing, freight) and an integrated software platform to manage supply chains. It uses a Cloud Supply Chain approach that combines physical logistics with digital tools to give real-time visibility, scalable capacity, and optimization across the entire supply chain. This makes it easier for both B2B and B2C clients to store, move, and fulfill orders efficiently while controlling costs. Compared to traditional logistics providers, STORD differentiates itself by tightly integrating software with logistics, offering real-time data and elastic capacity. The goal is to help brands build agile, connected, and cost-efficient supply chains.

Company size
1,001-5,000
Company stage
Debt Financing
Total funding
$1.2B
Headquarters
Union City, GA
Founded
2015

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